specified time horizon. -- Bootstrapping ; inflation ; inflation-indexed futures ; Mexico ; Value at Risk ; volatility …In this research paper ARCH-type models are applied in order to estimate the Value-at-Risk (VaR) of an inflation …-index futures portfolio for several time-horizons. The empirical analysis is carried out for Mexican inflation-indexed futures …

In this research paper ARCH-type models are applied in order to estimate the Value-at-Risk (VaR)of an inflation …-index futures portfolio for several time-horizons. The empirical analysis is carried out for Mexican inflation-indexed futures … bootstrapping simulations were applied. The results show that these models are relatively accurate for time horizons of one trading …

economic activity and inflation in Turkey during the 1991:7-2004:3 periods. In order to analyze these relationships, we have … stability tests. Besides, we have found out that the relationships between spread-real economic activity and spread-inflation …

In this paper, I apply univariate and vector autoregressive (VAR) models to forecast inflation in Vietnam. To … properties of inflation in Vietnam. Then, I compute the pseudo out-of-sample root mean square error (RMSE) as a measure of … forecasting models from among the different candidates. I find that VAR_m2 is the best monthly model to forecast inflation in …

We evaluate the ability of several univariate models to predict inflation in a number of countries and at several … DESARIMA models is high in stable inflation countries, for which the RMSPE is around 100 basis points when prediction is made …

In this paper, we study the fit and the predictive performance of the Phillips curve for euro area inflation with … regard to different inflation series, time periods and predictor variables, notably different global factors. We compare the … prices, global consumer inflation, global economic slack and foreign demand. We find that traditional global indicators such …

The difficulty in modelling inflation and the significance in discovering the underlying data generating process of … inflation is expressed in an ample literature regarding inflation forecasting. In this paper we evaluate nonlinear machine … learning and econometric methodologies in forecasting the U.S. inflation based on autoregressive and structural models of the …